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The Performance of an Autonomous Clustering Technique

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Classification, Clustering, and Data Analysis

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Abstract

Recently, a multi-agents system has been discussed in the field of adaptive control. An autonomous clustering is considered to be a multiple agents system which constructs clusters by moving each pair of objects closer or farther according to their relative similarity to all of the objects.

In this system, the objects correspond to autonomous agents, and the similarity relation is regarded as the environment. Defining a suitable action rule for the multi-agents, the clusters are constructed automatically.

In this paper, we discuss the ability of the detection of clusters by the autonomous clustering technique through the concrete examples.

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Author information

Authors and Affiliations

  1. Division of Systems and Information, Hokkaido University, Kita-13, Nishi-8, Kita-ku, Sapporo, 060-8628, Japan

    Yoshiharu Sato

Authors
  1. Yoshiharu Sato
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Editor information

Editors and Affiliations

  1. Wroclaw University of Economics, ul. Komandorska 118/120, 53-345, Wroclaw, Poland

    Krzysztof Jajuga

  2. Department of Statistics, Cracow University of Economics, ul. Rakowicka 27, 31-510, Cracow, Poland

    Andrzej Sokołowski

  3. Institute of Statistics, Technical University of Aachen, Wuellnerstrasse 3, 52056, Aachen, Germany

    Hans-Hermann Bock

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© 2002 Springer-Verlag Berlin Heidelberg

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Sato, Y. (2002). The Performance of an Autonomous Clustering Technique. In: Jajuga, K., Sokołowski, A., Bock, HH. (eds) Classification, Clustering, and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-56181-8_11

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  • DOI: https://doi.org/10.1007/978-3-642-56181-8_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43691-1

  • Online ISBN: 978-3-642-56181-8

  • eBook Packages: Springer Book Archive

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